






"""simple docstring"""





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_barthez import BarthezTokenizer
else:
  _SCREAMING_SNAKE_CASE   :							Tuple          =		None

_SCREAMING_SNAKE_CASE   :							List[Any]          =		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   :							Any          =		{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

_SCREAMING_SNAKE_CASE   :							int          =		{
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json'''
        ),
    },
}

_SCREAMING_SNAKE_CASE   :							Optional[int]          =		{
    '''moussaKam/mbarthez''': 1024,
    '''moussaKam/barthez''': 1024,
    '''moussaKam/barthez-orangesum-title''': 1024,
}

_SCREAMING_SNAKE_CASE   :							Tuple          =		'''▁'''






class 	a		(   lowercase__						):
    SCREAMING_SNAKE_CASE		:	Optional[int]		=					VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE		:	Optional[Any]		=					PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE		:	Any		=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE		:	int		=					["""input_ids""", """attention_mask"""]
    SCREAMING_SNAKE_CASE		:	Tuple		=					BarthezTokenizer






    def __init__(			self	:				int			,		__SCREAMING_SNAKE_CASE	:				List[Any]=None			,		__SCREAMING_SNAKE_CASE	:				List[str]=None			,		__SCREAMING_SNAKE_CASE	:				List[str]="<s>"			,		__SCREAMING_SNAKE_CASE	:				List[str]="</s>"			,		__SCREAMING_SNAKE_CASE	:				Optional[Any]="</s>"			,		__SCREAMING_SNAKE_CASE	:				List[str]="<s>"			,		__SCREAMING_SNAKE_CASE	:				List[Any]="<unk>"			,		__SCREAMING_SNAKE_CASE	:				Union[str, Any]="<pad>"			,		__SCREAMING_SNAKE_CASE	:				Dict="<mask>"			,		**__SCREAMING_SNAKE_CASE	:				Optional[Any]			,		)	->						Union[str, Any]:
      lowerCamelCase_       	=		AddedToken(SCREAMING_SNAKE_CASE_			,		lstrip=SCREAMING_SNAKE_CASE_			,		rstrip=SCREAMING_SNAKE_CASE_   ) if isinstance(SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_   ) else mask_token

      super().__init__(
          SCREAMING_SNAKE_CASE_			,		tokenizer_file=SCREAMING_SNAKE_CASE_			,		bos_token=SCREAMING_SNAKE_CASE_			,		eos_token=SCREAMING_SNAKE_CASE_			,		unk_token=SCREAMING_SNAKE_CASE_			,		sep_token=SCREAMING_SNAKE_CASE_			,		cls_token=SCREAMING_SNAKE_CASE_			,		pad_token=SCREAMING_SNAKE_CASE_			,		mask_token=SCREAMING_SNAKE_CASE_			,		**SCREAMING_SNAKE_CASE_			,		)

      lowerCamelCase_       	=		vocab_file
      lowerCamelCase_       	=		False if not self.vocab_file else True






    def   UpperCamelCase			(			self	:				Union[str, Any]			,		__SCREAMING_SNAKE_CASE	:				List[int]			,		__SCREAMING_SNAKE_CASE	:				Optional[List[int]] = None   )	->						List[int]:


      if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      lowerCamelCase_       	=		[self.cls_token_id]
      lowerCamelCase_       	=		[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep






    def   UpperCamelCase			(			self	:				Optional[int]			,		__SCREAMING_SNAKE_CASE	:				List[int]			,		__SCREAMING_SNAKE_CASE	:				Optional[List[int]] = None   )	->						List[int]:
      lowerCamelCase_       	=		[self.sep_token_id]
      lowerCamelCase_       	=		[self.cls_token_id]

      if token_ids_a is None:
        return len(cls + token_ids_a + sep   ) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep   ) * [0]






    def   UpperCamelCase			(			self	:				str			,		__SCREAMING_SNAKE_CASE	:				str			,		__SCREAMING_SNAKE_CASE	:				Optional[str] = None   )	->						Tuple[str]:


      if not self.can_save_slow_tokenizer:
        raise ValueError(
            'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
            'tokenizer.'   )

      if not os.path.isdir(SCREAMING_SNAKE_CASE_   ):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
        return
      lowerCamelCase_       	=		os.path.join(
          SCREAMING_SNAKE_CASE_			,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

      if os.path.abspath(self.vocab_file   ) != os.path.abspath(SCREAMING_SNAKE_CASE_   ):
        copyfile(self.vocab_file			,		SCREAMING_SNAKE_CASE_   )

      return (out_vocab_file,)






"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase        =				logging.get_logger(__name__)

UpperCAmelCase        =				{
    """shi-labs/nat-mini-in1k-224""": """https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json""",
    # See all Nat models at https://huggingface.co/models?filter=nat
}



class 			lowercase					( lowercase__   ,lowercase__		):
			lowercase        =     '''nat'''

			lowercase        =     {
			    '''num_attention_heads''': '''num_heads''',
			    '''num_hidden_layers''': '''num_layers''',
			}






			def __init__(self  :	Union[str, Any]      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=4      ,SCREAMING_SNAKE_CASE_  :	Dict=3      ,SCREAMING_SNAKE_CASE_  :	int=64      ,SCREAMING_SNAKE_CASE_  :	Tuple=[3, 4, 6, 5]      ,SCREAMING_SNAKE_CASE_  :	Dict=[2, 4, 8, 16]      ,SCREAMING_SNAKE_CASE_  :	Optional[int]=7      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=3.0      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=True      ,SCREAMING_SNAKE_CASE_  :	Any=0.0      ,SCREAMING_SNAKE_CASE_  :	List[Any]=0.0      ,SCREAMING_SNAKE_CASE_  :	Dict=0.1      ,SCREAMING_SNAKE_CASE_  :	Tuple="gelu"      ,SCREAMING_SNAKE_CASE_  :	str=0.02      ,SCREAMING_SNAKE_CASE_  :	str=1e-5      ,SCREAMING_SNAKE_CASE_  :	int=0.0      ,SCREAMING_SNAKE_CASE_  :	List[Any]=None      ,SCREAMING_SNAKE_CASE_  :	Tuple=None      ,**SCREAMING_SNAKE_CASE_  :	Union[str, Any]      ,)       ->	Tuple:





				"""simple docstring"""


				super().__init__(**SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  patch_size
				lowerCAmelCase												=  num_channels
				lowerCAmelCase												=  embed_dim
				lowerCAmelCase												=  depths
				lowerCAmelCase												=  len(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  num_heads
				lowerCAmelCase												=  kernel_size
				lowerCAmelCase												=  mlp_ratio
				lowerCAmelCase												=  qkv_bias
				lowerCAmelCase												=  hidden_dropout_prob
				lowerCAmelCase												=  attention_probs_dropout_prob
				lowerCAmelCase												=  drop_path_rate
				lowerCAmelCase												=  hidden_act
				lowerCAmelCase												=  layer_norm_eps
				lowerCAmelCase												=  initializer_range
				# we set the hidden_size attribute in order to make Nat work with VisionEncoderDecoderModel
				# this indicates the channel dimension after the last stage of the model
				lowerCAmelCase												=  int(embed_dim * 2 ** (len(SCREAMING_SNAKE_CASE_			) - 1)			)
				lowerCAmelCase												=  layer_scale_init_value
				lowerCAmelCase												=  ['''stem'''] + [F"""stage{idx}""" for idx in range(1      ,len(SCREAMING_SNAKE_CASE_			) + 1			)]
				lowerCAmelCase							,       lowerCAmelCase												=  get_aligned_output_features_output_indices(
				    out_features=SCREAMING_SNAKE_CASE_      ,out_indices=SCREAMING_SNAKE_CASE_      ,stage_names=self.stage_names			)


